US8107708B2 - Method for correcting truncation artifacts - Google Patents
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- US8107708B2 US8107708B2 US12/217,650 US21765008A US8107708B2 US 8107708 B2 US8107708 B2 US 8107708B2 US 21765008 A US21765008 A US 21765008A US 8107708 B2 US8107708 B2 US 8107708B2
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B6/03—Computed tomography [CT]
- A61B6/032—Transmission computed tomography [CT]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/46—Arrangements for interfacing with the operator or the patient
- A61B6/461—Displaying means of special interest
- A61B6/466—Displaying means of special interest adapted to display 3D data
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
- A61B6/5258—Devices using data or image processing specially adapted for radiation diagnosis involving detection or reduction of artifacts or noise
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
- G06T11/006—Inverse problem, transformation from projection-space into object-space, e.g. transform methods, back-projection, algebraic methods
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B6/027—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis characterised by the use of a particular data acquisition trajectory, e.g. helical or spiral
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2211/00—Image generation
- G06T2211/40—Computed tomography
- G06T2211/421—Filtered back projection [FBP]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2211/00—Image generation
- G06T2211/40—Computed tomography
- G06T2211/432—Truncation
Definitions
- the invention relates to a method for correcting truncation artifacts in a reconstruction method for computed tomography recordings.
- Such a correction method for truncation artifacts can be deployed with an x-ray diagnostic facility for angiography as known from US 2006/0120507 A1, which is shown by way of example in FIG. 1 .
- the x-ray diagnostic facility has a C-arm 2 supported in a rotatable manner on a stand 1 , at the end of which C-arm 2 an x-ray radiation source, for example an x-ray emitter 3 , and an x-ray image detector 4 are positioned.
- the x-ray image detector 4 can be a rectangular or square, flat semiconductor detector, which is preferably made of amorphous silicon (aSi).
- a patient support table 5 for recording for example the heart of a patient to be examined.
- an image system 6 Connected to the x-ray diagnostic facility is an image system 6 , which receives and processes the image signals from the x-ray image detector 4 . The x-ray images can then be viewed on a monitor 7 .
- the movable components 2 to 5 can also be supported individually or in a common manner on robot arms.
- the examination object 9 can be for example an animal or human body or even a phantom body.
- the x-ray radiation source 2 and the x-ray image detector 4 move respectively around the examination object 9 in such a manner that the x-ray radiation source 2 and the x-ray image detector 4 are located facing each other on opposite sides of the examination object 9 .
- a significant processing step for the 3D reconstruction by means of filtered backprojection (FBP) is the filtering of the projection data along predefined lines in the x-ray image detector.
- the non-local nature of the filter core for example the ramp filter or Hilbert filter, means that the filter lines have to run through the entire projection of the examination region and cannot be cut off, even if only part of the body region, for example the so-called region of interest (ROI), is to be reconstructed.
- ROI region of interest
- the limited detector width results in cut off projections of the examination region in many recordings, in particular when using the above-mentioned C-arm system, as this cannot be covered completely by the field of view (FoV). This results in cut-off filter lines in these projections.
- This is an examination of the abdomen or thorax.
- Transaxial truncation is produced by examination objects that are cut off along the horizontal detector axis.
- Axial truncation is produced by examination objects that are cut off along the vertical detector axis. Therefore in the case of the Feldkamp algorithm described in [1], with which filtering operates along horizontal lines in the x-ray image detector, only transaxial truncation of the filter lines is possible.
- the development of new approximative and exact reconstruction algorithms and the use of novel scanning paths, such as circle and line, circle and arc, saddle means that non-horizontal filter lines have also been introduced, as described for example in Pack et al. [2] and [6], Katsevich [3] and [4] as well as Nett et al. [5]. This means that both transaxial truncation and axial truncation can occur (see also FIG. 3 ).
- FIG. 3 shows possible truncations for non-horizontal filter lines by way of example.
- the contours of the examination object are mapped on the x-ray image detector 4 .
- One filter line F 1 is cut off transaxially on both sides.
- One filter line F 2 is cut off axially on both sides.
- One filter line F 3 is cut off axially on the left and transaxially on the right.
- One filter line F 4 has no truncation. Truncation always occurs when a filter line exits from the x-ray image detector 4 before it exits from the examination object 9 .
- Significant reconstruction artifacts result for every point on a truncated filter line. This can be the case for the majority of points in the case of non-horizontal filter lines.
- Hybrid correction is made up of the so-called water cylinder correction and a Gaussian extrapolation, as described by way of example in Hsieh et al. [7], Zellerhoffet al. [8] or Scholz [9]. The method is implemented row by row. It is first checked in each instance using a threshold value whether truncation is present.
- water cylinder correction or Gaussian extrapolation is used, depending on the gradient of the (truncated) projection profile at the edge of the detector row in question (see FIG. 4 ). If the gradient at the left detector edge is positive or the gradient at the right detector edge is negative, water cylinder correction is deployed (see FIG. 5 ). With water cylinder correction it is assumed that the examination object can be approximated very closely by a water cylinder. To this end the center point and radius of the water cylinder are first determined. The missing projection values are then generated artificially by computer-simulated x-ray beams, which pass through the water cylinder. The detector row is continued with the projection values thus generated.
- Gaussian extrapolation is deployed (see FIG. 6 ). With Gaussian extrapolation the missing projection values are approximated by a Gaussian curve. This produces the absent projection values, as with water cylinder correction.
- a Feldkamp based reconstruction algorithm is also used with CT systems.
- filtering takes place along non-horizontal lines in the x-ray image detector 4 , with the gradients of the filter lines having very low values.
- CT systems transaxial truncation cannot take place due to the size of the detector. Therefore only axial truncation has to be dealt with.
- the x-ray image detector 4 is constantly continued in the axial direction, by repeatedly copying and adding the first and/or last detector row (see FIG. 7 ) as for example with Flohr et al. [10] or Kachelrie ⁇ et al. [11].
- FIG. 4 shows a projection profile p(u) along a cut off detector row. Either water cylinder correction (a) or Gaussian extrapolation (b) is used depending on the gradient of the measured projection values 11 at the edge of the row.
- FIG. 6 shows an example of Gaussian extrapolation for the right detector edge 36 .
- the missing projection values are approximated by a Gaussian curve 14 and used as artificially generated projection values 15 to continue the profile.
- Section 2.D deals with an extrapolation method, which supplements missing data (see FIG. 5 , mask 1 ).
- the missing data at the start and end of the scanning path is the result of data sorting from fan-beam to parallel-beam geometry regardless of the shape of the object and the size of the detector.
- the resulting truncation problem is however equivalent to transaxial truncation and is corrected accordingly.
- the invention is based on the object of configuring a correction method for truncation artifacts of the type mentioned in the introduction, such that truncation correction can also be carried out even with filter lines of any orientation.
- the method corrects truncation artifacts in a reconstruction method for computed tomography recordings with truncated projection data in the reconstructed computed tomography images, wherein a radiation source emits divergent radiation, an object to be examined is transilluminated in different projection directions with said divergent radiation, the radiation penetrating the object to be examined is detected by an x-ray image detector and a filtered backprojection is carried out filtering the projection data along predefined non-horizontal lines in the x-ray image detector, with projection images recorded by the x-ray image detector being extended by determining the attenuation of the radiation outside the projection image for pixels.
- the object is achieved in that for the purposes of truncation correction non-horizontal filter lines are extended by a transaxial and axial artificial extension of the x-ray image detector, with the truncation correction for non-horizontal filter lines being carried out according to a method from at least one of the following groups:
- Truncation correction takes place as a function of the specific position and orientation of the filter lines, with the filter lines themselves being retained.
- Truncation correction takes place by introducing new modified filter lines, with filtering taking place along offset artificially extended filter lines.
- the truncation correction methods for non-horizontal filter lines are divided into three groups.
- the methods in group I carry out the correction regardless of the specific position and orientation of the filter lines. They can therefore be applied regardless of the reconstruction algorithm used.
- the methods in group II carry out the correction as a function of the specific position and orientation of the filter lines.
- the filter lines themselves are retained. With the method in group III new filter lines are introduced during the course of truncation correction.
- the filter lines according to group II) can be artificially extended by constant continuation of the x-ray image detector in the axial direction followed by hybrid correction along the filter lines or a modified water cylinder correction along the filter lines.
- the new methods allow an artifact-free ROI reconstruction within larger body regions such as the abdomen or thorax, which was not possible until now due to the restricted detector surface (in particular with C-arm systems). Moreover the methods can expediently be combined with all FPB algorithms, with which cut off projections cause artifacts.
- the methods hereby principally aim toward novel approximative and exact FBP algorithms, having non-horizontal filter lines.
- Methods 1 and 2 are independent of the reconstruction algorithm and can be seen as a preprocessing step before reconstruction. They are therefore generally valid.
- Methods 3 to 6 are a function of the specific reconstruction algorithm but can however be integrated effectively herein. Moreover the new methods allow an enlargement of the FoV and therefore the reconstruction of larger body regions.
- FIG. 1 shows an x-ray diagnostic facility for implementing the method
- FIG. 2 shows a view of the path of an x-ray image detector and a radiation source around an object to be examined in an axial viewing direction
- FIG. 3 shows an overview to explain transaxial and axial truncation and possible types of filter line
- FIG. 4 shows a projection profile p(u) along a cut off detector row
- FIG. 5 shows a projection profile p(u) with a water cylinder correction for the right detector edge
- FIG. 6 shows a projection profile p(u) with a Gaussian extrapolation at the right detector edge
- FIG. 7 shows a truncation correction by constant continuation of the x-ray image detector in the axial direction
- FIG. 8 shows an original projection with axial and transaxial truncation as a basis for explaining method 1,
- FIG. 9 shows transaxial extension of the x-ray image detector according to FIG. 8 by means of hybrid correction
- FIG. 10 shows axial extension of the x-ray image detector according to FIG. 9 by means of hybrid correction
- FIG. 11 shows an original projection with axial and transaxial truncation as a basis for explaining method 2
- FIG. 12 shows transaxial extension of the x-ray image detectors according to FIG. 11 by means of hybrid correction
- FIG. 13 shows axial extension by means of constant continuation of the x-ray image detector according to FIG. 12 in the axial direction
- FIG. 14 shows an original projection and a filter line according to method 3 with associated projection profile
- FIG. 15 shows an original projection and filter line according to method 4 with associated projection profile
- FIG. 16 shows an original projection and filter line according to method 5 with associated projection profile und
- FIG. 17 shows an original projection and the original and modified filter line according to method 5 with associated projection profile.
- FIG. 8 shows the original projection with axial and transaxial truncation.
- the x-ray image detector 4 has first been extended transaxially with the aid of hybrid correction, so that extension regions with attenuated transaxial continuation 17 result on both sides.
- the x-ray image detector 4 has then been extended axially with the aid of hybrid correction, so that extension regions with attenuated transaxial continuation 18 result on both sides.
- the size of the extension regions can be configured freely in each instance and can be selected so that it is different for each detector side (left, right, top, bottom). Further flexibility of the method means that steps b) and c) can be interchanged.
- FIG. 11 shows the original projection with axial and transaxial truncation.
- the x-ray image detector 4 has first been extended with the aid of hybrid correction so that extension regions with attenuated transaxial continuation 17 result on both sides.
- the x-ray image detector 4 has then been extended axially by repeatedly copying and adding the first and last detector rows, so that extension regions with constant axial continuation 19 result on both sides.
- the size of the extension region can be configured freely in each instance and can be selected so that it is different for each detector side (left, right, top, bottom).
- the axial extension regions 19 should hereby be set so that no further filter lines are cut off. Further flexibility of the method means that steps b) and c) can be interchanged.
- FIG. 14 shows the original projection and a filter line F 3 , which is cut off axially on the left and transaxially on the right.
- Curve 20 shows the corresponding projection profile p(u) for this filter line F 3 .
- the profile has been continued on both sides by artificially generated projection values 22 by means of hybrid correction.
- the size of the extension region can be configured freely in each instance and can be selected so that it is different for each side of a filter line F 3 .
- FIG. 15 shows the original projection, which has already been supplemented by extension regions with constant axial continuation 23 in the axial direction.
- the projection profile p(u) of the filter line F 3 therefore only shows transaxial truncation.
- the profile has been continued by artificially generated projection values 26 with the aid of hybrid correction.
- Continuation 27 of the supplemented curve 25 results in the region of constant axial continuation 23 .
- the sizes of the extension regions for the x-ray image detector 4 and filter lines F 3 can be freely configured in each instance and can be selected so that they are different for each detector side (top, bottom) and for each side of a filter line F 3 .
- FIG. 16 shows the original projection together with the projection of a water cylinder 28 .
- the projection profile p(u) of the filter line F 5 only has transaxial truncation in this example.
- the profile of the filter line F 5 has been continued by means of artificially generated projection values 31 , in that the filter line F 5 has been evaluated in this region along the projection of the water cylinder 28 .
- the corresponding projection values are artificially generated by computer-simulated x-ray beams.
- the center axis (or rotation axis) of the cylinder is oriented parallel to the z-axis of the reference coordinate system.
- the height of the cylinder is assumed to be infinite, so that only the point of intersection (x, y, 0) of the center axis of the cylinder with the xy-plane and the radius R of the cylinder have to be determined.
- d refers to the sectional length of the x-ray beam with the water cylinder, d′ and d′′ its first and second derivation in relation to u and ⁇ w the attenuation coefficient of water.
- the procedure should be applied anew for each side of a filter line F 5 .
- the modified water cylinder correction differs from the original water cylinder correction in the use of cone-beam geometry. In the original method parallel beam geometry is used to generate the projection values, even though the original projections are acquired using cone-beam geometry.
- FIG. 17 shows the original projection together with the original filter line F 3 and the modified filter line F 6 shown with a broken line.
- the curve 32 of the projection profile p(u) of the modified filter line F 6 only has transaxial truncation.
- the profile has been continued with artificially generated projection values 34 with the aid of hybrid correction.
- the sizes of the extension regions for the filter lines can be freely configured in each instance and can be selected so that they are different for each side of a filter line.
- the x-ray image detector 4 is artificially extended transaxially and axially.
- the extension is based on hybrid correction in each instance (see example 1).
- the x-ray image detector 4 is artificially extended transaxially and axially.
- the transaxial extension is based on hybrid correction.
- the axial extension happens by means of constant continuation of the x-ray image detector 4 in the axial direction (see also FIG. 5 ), by repeatedly copying and adding the first and last detector rows (see example 2).
- the filter lines are artificially extended in that the hybrid correction is carried out not along the detector rows as in the original method (see also image 2 ) but along the filter lines (see example 3).
- the filter lines are artificially extended, by constant continuation of the x-ray image detector 4 in the axial direction (see also FIG. 5 ) followed by hybrid correction along the filter lines (see example 4).
- the filter lines are artificially extended, by carrying out a modified water cylinder correction along the filter lines (see example 5).
- the filter lines are modified in such a manner that filtering takes place along offset filter lines. These are then artificially extended, by carrying out the hybrid correction along the offset filter lines (see example 6).
- the filter part of the filtered backprojection consists of a one-dimensional linear filtering of the detector data.
- the data can be filtered by means of a convolution operation in real space. Alternatively a convolution operation in real space can be replaced by a multiplication in reciprocal space.
- single-row detectors it is clear that the whole detector row is dealt with in one filter step.
- multi-row detectors surface detectors
- the data to be filtered is collected along one filter line.
- the data along one filter line can either be convoluted in real space or multiplied in reciprocal space. It should be noted that only the part of real space along a filter line is transformed to reciprocal space with a one-dimensional Fourier transformation.
- the selection of the filter lines is a function of the reconstruction problem and the reconstruction algorithm used.
- the frequently applied Feldkamp algorithm described in [1] filters the detector data one-dimensionally row by row, i.e. the filter lines are oriented along the detector rows.
- the algorithms for an exact reconstruction of cone-beam data filter lines are generally not arranged along the detector rows, as described for example in [2] to [6].
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Abstract
Description
d(u 0 ,x,yR)*μw =p(u 0) (1)
d′(u 0 ,x,y,R)*μw =p′(u 0) (2)
d″(u 0 ,x,y,R)*μw =p″(u 0). (3)
- [1] L. A. Feldkamp, L. C. Davis, J. W. Kress. “Practical Cone-Beam Algorithm”. J. Opt. Soc. Am. A, 1(6): pages 612-619, 1984.
- [2] J. Pack, F. Noo, and H. Kudo. “Investigation of saddle trajectories for cardiac ct imaging in cone-beam geometry”. Physics in Medicine and Biology, 49(11): pages 2317-2336, 2004.
- [3] A. Katsevich. “Image reconstruction for the circle-and-line trajectory”. Physics in Medicine and Biology, 49(22): pages 5059-5072, 2004.
- [4] A. Katsevich. “Image reconstruction for the circle-and-arc trajectory”. Physics in Medicine and Biology, 50(10): pages 2249-2265, 2005.
- [5] B. E. Nett, T. Zhuang, and G.-H. Chen. “A cone-beam fbp reconstruction algorithm for short-scan and super-short-scan source trajectories”. In Fully 3D Image Reconstruction in Radiology and Nuclear Medicine, Salt Lake City, Utah, USA, Jul. 6-Jul. 9, 2005.
- [6] J. Pack and F. Noo. Cone-beam reconstruction using 1D filtering along the projection of m-lines. Inverse Problems, 21(3): pages 1105-1120, 2005.
- [7] J. Hsieh, E. Chao, J. Thibault, B. Grekowicz, A. Horst, S. McOlash, and T. J. Myers. A novel reconstruction algorithm to extend the CT scan field-of-view. Medical Physics, 31(9): pages 2385-2391, 2004
- [8] M. Zellerhoff, B. Scholz, E.-P. Rührnschopf and T. Brunner. Low contrast 3D-reconstruction from C-arm data. SPIE Medical Imaging 2005, 5745: pages 1605-7422, 2005
- [9] Bernhard Scholz, Fächerstrahlbasierte Wasserzylinderextrapolation von abgeschnittenen Projektionen zur Behandlung von Trunkierungsartefacten (Fan-beam based water cylinder extrapolation from cut-off projections for dealing with truncation artifacts), former
patent application DE 10 2006 014 629.8 dated 29.03.2006. - [10] T. Flohr, K. Stierstorfer, H. Bruder, J. Simon, A. Polacin, and S. Schaller. Image reconstruction and image quality evaluation for a 16-slice CT scanner. Medical Physics, 30(5): pages 832-845, 2003
- [11] M. Kachelrieβ, M. Knaup, and W. A. Kalender. Extended parallel backprojection for standard three-dimensional and phase-correlated four-dimensional axial and spiral cone-beam CT with arbitrary pitch, arbitrary cone-angle, and 100% dose usage. Medical Physics, 31(6): pages 1623-1641, 2004
- [12] Magnusson et al., “Handling of Long Objects in Iterative Improvement of Nonexact Reconstruction in Helical Cone-Beam CT”, IEEE Trans. Med. Imaging Vol. 25, NO. 7, July 2006, pages 935-940
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US9483870B2 (en) | 2012-04-27 | 2016-11-01 | Infinitt Healthcare Co., Ltd. | Apparatus for processing, generating, storing and displaying images in picture archiving communication system, and method thereof |
US11995746B2 (en) | 2018-12-12 | 2024-05-28 | Koninklijke Philips N.V. | System for reconstructing an image of an object |
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CN101558456B (en) | 2006-12-19 | 2013-07-24 | 陶氏环球技术公司 | Improved composites and methods for conductive transparent substrates |
DE102009042922B4 (en) | 2009-09-24 | 2019-01-24 | Siemens Healthcare Gmbh | Method and apparatus for image determination from x-ray projections taken when traversing a trajectory |
US9087404B2 (en) * | 2010-05-27 | 2015-07-21 | Koninklijke Philips N.V. | Reconstruction for cone-beam computed tomography imaging with off-center flat panel detector |
DE102010026374A1 (en) | 2010-07-07 | 2012-01-12 | Siemens Aktiengesellschaft | Method for the reconstruction of a three-dimensional image data set and X-ray device |
US8913710B2 (en) * | 2011-04-27 | 2014-12-16 | Varian Medical Systems, Inc. | Truncation correction imaging enhancement method and system |
DE102018221943A1 (en) * | 2018-12-17 | 2020-06-18 | Siemens Healthcare Gmbh | Artifact correction method for three-dimensional volume image data |
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